MIXED-GRASS PRAIRIE PASSERINES EXHIBIT WEAK AND VARIABLE RESPONSES TO PATCH SIZE
Bibliographic record
Abstract
Much of our current understanding of the demographic effects of habitat fragmentation on bird populations is derived from studies of passerines in forests and tallgrass prairie surrounded by woody vegetation. We quantified grassland bird density, nest survival, and productivity in 41 native mixed-grass prairie pastures during 1997-2000 in southern Saskatchewan, Canada. Pastures ranged in size from 18 ha to 11,600 ha and were typically surrounded by agriculture (i.e., ranching and annual cropping). Grassland passerines did not respond strongly or uniformly to patch size. Sprague's Pipit (Anthus spragueii) was the only species whose density increased with pasture size. Patch size had minimal influence on nest survival of Sprague's Pipit or Clay-colored Sparrow (Spizella pallida); whereas nest survival increased with patch size for Savannah Sparrow (Passerculus sandwichensis) and declined for Baird's Sparrow (Ammodramus bairdii), Chestnut-collared Longspur (Calcarius ornatus), and Western Meadowlark (Sturnella neglecta). Time-specific factors (i.e., nest age, date, and year) were more important predictors of nest survival than patch size. Exploratory analyses indicated that effects of edge distance, pasture shape, or landscape on nest survival were just as likely as patch-size effects. However, effects of edge on Chestnut-collared Longspurs may be governed by landscape-level factors, because nest survival decreased with distance to edge in landscapes with increased amounts of cropland. Our results indicate that mixed-grass prairie parcels ≥18 ha play a role in the conservation of several grassland passerine species currently in decline, but the conservation of Sprague's Pipit likely depends on maintaining larger tracts of native prairie. Les Passereaux des Prairies Herbacées Montrent des Réponses Faibles et Variables en Réponse à la Taille des Parcelles d'Habitats
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".